Hearing aid users encounter many different acoustic environments in daily life. While these environments usually contain a variety of desired sounds such as speech, music, and naturally occurring low-level sounds, they often also contain variable levels of undesirable noise.
The characteristics of such noise in a particular environment can vary widely. For example, noise may originate from one direction or from many directions. It may be steady, fluctuating, or impulsive. It may consist of single frequency tones, wind noise, traffic noise, or broadband speech babble.
Users often prefer to use hearing aids that are designed to improve the perception of desired sounds in different environments. This typically requires that the hearing aid be adapted to optimize a user's hearing in both quiet and loud surroundings. For example, in quiet, improved audibility and good speech quality are generally desired; in noise, improved signal to noise ratio, speech intelligibility and comfort are generally desired.
Many traditional hearing aids are designed with a small number of programs optimized for specific situations, but users of these hearing aids are typically required to manually select what they think is the best program for a particular environment. Once a program is manually selected by the user, a signal processing strategy associated with that program can then be used to process signals derived from sound received as input to the hearing aid.
Unfortunately, manually choosing the most appropriate program for any given environment is often a difficult task for users of such hearing aids. In particular, it can be extremely difficult for a user to reliably and quickly select an optimal program in rapidly changing acoustic environments.
The advent of digital hearing aids has made possible the development of various methods aimed at assessing acoustic environments and applying signal processing to compensate for adverse acoustic conditions. These approaches generally consist of auditory scene classification and application of appropriate signal processing schemes. Some of these approaches are known and disclosed in the references described below.
For example, International Publication No. WO 01/20965 A2 discloses a method for determining a current acoustic environment, and use of the method in a hearing aid. While the publication describes a method in which certain auditory-based characteristics are extracted from an acoustic signal, the publication does not teach what functionality is appropriate when specific auditory signal parameters are extracted.
Similarly, International Publication No. WO 01/22790 A2 discloses a method in which certain auditory signal parameters are analyzed, but does not specify which signal processing methods are appropriate for specific auditory scenes.
International Publication No. WO 02/32208 A2 also discloses a method for determining an acoustic environment, and use of the method in a hearing aid. The publication generally describes a multi-stage method, but does not describe the nature and application of extracted characteristics in detail.
U.S. Publication No. 2003/01129887 A1 describes a hearing prosthesis where level-independent properties of extracted characteristics are used to automatically classify different acoustic environments.
U.S. Pat. No. 5,687,241 discloses a multi-channel digital hearing instrument that performs continuous calculations of one or several percentile values of input signal amplitude distributions to discriminate between speech and noise in order to adjust the gain and/or frequency response of a hearing aid.